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An Application of Linear Mixed Effect Model to Compare the Drug Treatment Effect in Patients with Type 2 Diabetes


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1 Dept. of Statistics, Gauhati University
     

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In this article, different types of mixed effect models have been applied for drug effect comparison in type 2 diabetes patients. The mixed effect models have been applied through Bayesian approach and compared with frequency approach. The combination of metformin with pioglitazone is found to be effective compared to pioglitazone with gliclazide.

Keywords

MCMC, FBS, AR(1)
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  • Metformin/glibenclamide (Glucovance) for type 2 diabetes mellitus avliable at Rational Assessment of Drugs and Research.2010.
  • Antonio Ceriello and Don Johns, Mario Widel, David J. Eckland, Kathryn and Meng. Comparison of Effect of Pioglitazone With Metformin or Sulfonylurea (Monotherapy and Combination Therapy) on Postload Glycemia and Composite Insulin Sensitivity Index During an Oral Glucose Tolerance Test in Patients With Type 2 Diabetes. Diabetes Care 28:266–272, 2005.
  • Laird, N. M. and Ware, J. H. (1982). Random effects models for longitudinal data. Biometrics 1982: 38:963–974.
  • Wong, G. Y. and Mason, W. M. The hierarchical logistic regression model for multilevel analysis. Journal of the American Statistical Association 1985: 80, 513–524.
  • West, M. Generalized linear models: Scale parameters, outlier accommodation and prior distributions. In J. M. Bernardo, M. H. DeGischolar_main, D. V. Lindley, and A. F. M. Smith (eds.),1985.
  • Harville,David A(1977) “Maximum Likelihood Approaches to variance component Estimation and to Related Problem:Journal of the American Statistical Association; Vol 72,No.358.
  • Kerl M, Martins M, Churchill G. Analysis of variance for gene expression, micro array data. J comput Biol.2000;7:819-837.
  • Andrew Gelman(1995)Method of moments using Monter Carlo simulation. Journal of Computatuional and Graphical Statistics,36-54.
  • Brown H and Prescott R. Applied mixed models in Medicine; 2006 John Wiley & Sons,Ltd.
  • Horrace .C and Schmidt P.(2000) Multiple comparison with the best, with economic applications. J. Appl. Econometrics 15,1-26.
  • Butler, S. and Louis, T. (1992). Random effects models with non-parametric priors. Stat. in Med.11, 1981±2000.
  • Escobar, M. and West, M. (1998) Computing nonparametric hierarchical models. In: Dey, D. et al. (eds.) Practical Nonparametric and Semiparametric Bayesian Statistics. New York, NY:Springer.
  • Spiegelhalter,D.J., Thomas,A.,Best,N. and Lunn,D(2004) WinBUGS 1.4 User Manual, Version 1.4.1.Cambridge Medical Research Council Biostatistics Unit.
  • Zhu,L. and Carlin, B.P(2000) Comparing hierarchical models for spatio-temporally misaligned data using deviance information criterion. Statistics in Medicine,19,2265-2278.

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  • An Application of Linear Mixed Effect Model to Compare the Drug Treatment Effect in Patients with Type 2 Diabetes

Abstract Views: 381  |  PDF Views: 0

Authors

Dilip C. Nath
Dept. of Statistics, Gauhati University
Atanu Bhattacharjee
Dept. of Statistics, Gauhati University

Abstract


In this article, different types of mixed effect models have been applied for drug effect comparison in type 2 diabetes patients. The mixed effect models have been applied through Bayesian approach and compared with frequency approach. The combination of metformin with pioglitazone is found to be effective compared to pioglitazone with gliclazide.

Keywords


MCMC, FBS, AR(1)

References